Predicting blood flow near hepatic tumors with ultrasound to improve RF ablations

描述(申请人提供)：[目的本研究旨在提高射频消融术的肝癌根治率，增加候选患者的数量。射频消融治疗小于3 cm的原发性或继发性恶性肝肿瘤患者的局部肿瘤清除率超过83%；不幸的是，大多数患者的肿瘤大于3 cm。由于射频设备在不同患者之间甚至同一患者内部造成的热损伤大小的不可预测的差异，较大肿瘤的局部肿瘤根除成功率降至不到50%。成功率受到局部血流的限制，因为局部血流带走了治疗过程中施加的热量，这可能导致一些肿瘤细胞无法达到55摄氏度的细胞死亡温度，并导致疾病的不良延续和传播。目的本研究开发了一种利用三维超声图像定量肿瘤周围感兴趣区(ROI)血流量的新方法。血流信息将被评估为射频消融设备性能的预测指标，供临床医生在消融计划期间使用，以确保所有肿瘤细胞被摧毁，并将健康组织的干扰降至最低(对 肝硬变)。方法开发基于软件的算法，从三维超声图像重建患者特定的肝血管几何形状。来自患者血管内的相关多普勒颜色/速度数据将与角度校正的血管几何形状相结合，以建立临床医生在肿瘤周围设定的ROI内的“血流影响指数”。该指数将提供局部血流的数量和方向的指示。算法功能将通过在正常和病理流速范围内的已知几何形状的解剖学上正确的肝脏血流模型来验证。这些算法的预测能力将通过对废弃的牛肝进行计划和测试消融，以及比较计划的和实际的消融大小来验证。]

DESCRIPTION (provided by applicant): [Aim The proposed research is intended to increase the liver cancer tumor eradication rate of Radiofrequency (RF) ablation and increase the number of candidate patients. Relevance The local tumor eradication rate for patients with primary or secondary malignant liver tumors smaller than 3cm who are treated using Radiofrequency (RF) ablation is over 83%; unfortunately, the majority of patients have tumors larger than 3cm. The success rate of local tumor eradication of larger tumors falls to less than 50% due to unpredictable variation in the size of the thermal injury created by RF devices between different patients and even within the same patient. The success rates are limited by local blood flow carrying away the heat applied during treatment which can result in some tumor cells not reaching the cell death temperature of 55¿C and an undesired continuation and propagation of the disease. Objective The proposed research develops a new method of quantifying the amount of blood flow within a Region of Interest (ROI) surrounding a tumor using 3D ultrasound imagery. The flow information will be evaluated as a predictor of RF ablation device performance for use by clinicians during ablation planning to ensure that all of the tumor cells are destroyed and a minimal amount of healthy tissue is disturbed (critical for patients with cirrhosis). Methods Software based algorithms will be developed to reconstruct patient specific liver vessel geometry from 3D ultrasound Imagery. The associated Doppler color/velocity data from within the patient vessels will be combined with angle corrected vessel geometry to establish a "Flow Influence Index" within the ROI set around the tumor by the clinician. The index will provide an indication of the amount and direction of local blood flow. The algorithm function will be verified with an anatomically correct liver flow model of known geometry over a range of normal and pathological flow rates. The predictive capability of the algorithms will be validated by planning and performing test ablations on discarded cattle livers and comparing the planned and actual ablation sizes.]